OpenRaiser/Intern-Atlas huggingface dataset:
On the Properties of Cubic Metric for OFDM Signals
Venue: arXiv cs.IT 2015
Year: 2015

As a metric for amplitude fluctuation of orthogonal frequency division multiplexing (OFDM) signal, cubic metric (CM) has received an increasing attention because it is more closely related to the distortion induced by nonlinear devices than the well-known peak-to-average power ratio (PAPR). In this paper, the properties of CM of OFDM signal is investigated. First, asymptotic distribution of CM is derived. Second, it is verified that 1.7 times oversampling rate is good enough to capture the CM of continuous OFDM signals in terms of mean square error, which is also practically meaningful because the fast Fourier transform size is typically 1.7 times larger than the nominal bandwidth in the long-term evolution (LTE) of cellular communication systems.
A Strategy for Power System Stability Improvement via Controlled Charge/Discharge of Plug-in Electric Vehicles
Venue: arXiv cs.SY 2015
Year: 2015

Plug-in electrical vehicles (PEV) are capable of both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) power transfer. The advantages of developing V2G include an additional revenue stream for cleaner vehicles, increased stability and reliability of the electric grid, lower electric system costs, and eventually, inexpensive storage and backup for renewable electricity. Here we show how smart control of PEVs can improve the stability of power grids using only local frequency measurements. We evaluate the proposed control strategy on the IEEE Case 3 and the IEEE New England power systems. The results show that V2G leads to improved steady-state stability, larger region of stability, reduced frequency and voltage fluctuations during transients and longer critical clearing times.
Toward Simulation-free Estimation of Critical Clearing Time
Venue: arXiv cs.SY 2015
Year: 2015

Contingency screening for transient stability of large-scale, strongly nonlinear, interconnected power systems is one of the most computationally challenging parts of Dynamic Security Assessment and requires huge resources to perform time-domain simulations-based assessment. To reduce computational cost of time-domain simulations, direct energy methods have been extensively developed. However, these methods, as well as other existing methods, still rely on time-consuming numerical integration of the fault-on dynamics. This task is computationally hard, since possibly thousands of contingencies need to be scanned and thousands of accompanied fault-on dynamics simulations need to be performed and stored on a regular basis. In this paper, we introduce a novel framework to eliminate the need for fault-on dynamics simulations in contingency screening. This simulation-free framework is based on bounding the fault-on dynamics and extending the recently introduced Lyapunov Function Family approach for transient stability analysis of structure-preserving model. In turn, a lower bound of the critical clearing time (CCT) is obtained by solving convex optimization problems without relying on any time-domain simulations. A comprehensive analysis is carried out to validate this novel technique on a number of IEEE test cases.
Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks
Venue: arXiv cs.CE 2015
Year: 2015

Financial news contains useful information on public companies and the market. In this paper we apply the popular word embedding methods and deep neural networks to leverage financial news to predict stock price movements in the market. Experimental results have shown that our proposed methods are simple but very effective, which can significantly improve the stock prediction accuracy on a standard financial database over the baseline system using only the historical price information.
Scientific Modelling with Coalgebra-Algebra Homomorphisms
Venue: arXiv cs.LO 2015
Year: 2015

Many recursive functions can be defined elegantly as the unique homomorphisms, between two algebras, two coalgebras, or one each, that are induced by some universal property of a distinguished structure. Besides the well-known applications in recursive functional programming, several basic modes of reasoning about scientific models have been demonstrated to admit such an exact meta-theory. Here we explore the potential of coalgebra--algebra homomorphism that are not a priori unique, for capturing more loosely specifying patterns of scientific modelling. We investigate a pair of dual techniques that leverage (co)monadic structure to obtain reasonable genericity even when no universal properties are given. We show the general applicability of the approach by discussing a surprisingly broad collection of instances from real-world modelling practice.
Selecting the Best Traffic Scheme for the Bicutan Roundabout: A Microsimulation Approach with Multiple Driver-Agents
Venue: arXiv cs.CE 2015
Year: 2015

We present the result of our microsimulation study on the effects of six traffic schemes $T=\{t_0, t_1, \dots, t_5\}$ on the mean total delay time ($Δ$) and mean speed ($Σ$) of vehicles at the non-signalized Bicutan Roundabout (BR) in Upper Bicutan, Taguig City, Metro Manila, with $t_0$ as the current traffic scheme being enforced and $t_{i>0}$ as the proposed ones. We present first that our simulation approach, a hybridized multi-agent system (MAS) with the car-following and lane-changing models (CLM), can mimic the current observed traffic scenario $C$ at a statistical significance of $α=0.05$. That is, the respective absolute differences of the $Δ$ and $Σ$ between $C$ and $t_0$ are not statistically different from zero. Next, using our MAS-CLM, we simulated all proposed $t_{i>0}$ and compared their respective $Δ$ and $Σ$. We found out using DMRT that the best traffic scheme is $t_3$ (i.e., when we converted the bi-directional 4-lane PNR-PNCC road into a bi-directional 1-lane PNR-to-PNCC and 3-lane PNCC-to-PNR routes during rush hours). Then, we experimented on converting BR into a signalized junction and re-implemented all $t_3$ with controlled stops of $S=\{15s, 45s\}$. We found out that $t_3$ with a 15-s stop has the best performance. Finally, we simulated the effect of increased in vehicular volume $V$ due to traffic improvement and we found out that $t_3$ with 15-s stop still outperforms the others for all increased in $V=\{10\%, 50\%, 100\%\}$.
Fast 3D Synthetic Aperture Radar Imaging from Polarization-Diverse Measurements
Venue: arXiv cs.IT 2015
Year: 2015

An innovative 3-D radar imaging technique is developed for fast and efficient identification and characterization of radar backscattering components of complex objects, when the collected scattered field is made of polarization-diverse measurements. In this context, all the polarimetric information seems irretrievably mixed. A direct model, derived from a simple but original extension of the widespread "multiple scattering model" leads to a high dimensional linear inverse problem. It is solved by a fast dedicated imaging algorithm that performs to determine at a time three huge 3-D scatterer maps which correspond to HH, VV and HV polarizations at emission and reception. It is applied successfully to various mock-ups and data sets collected from an accurate and dedicated 3D spherical experimental layout that provides concentric polarization-diverse RCS measurements.
Indoor Location Estimation with Optical-based OFDM Communications
Venue: arXiv cs.IT 2015
Year: 2015

Visible Light Communication (VLC) using light emitting diodes (LEDs) has been gaining increasing attention in recent years as it is appealing for a wide range of applications such as indoor positioning. Orthogonal frequency division multiplexing (OFDM) has been applied to indoor wireless optical communications in order to mitigate the effect of multipath distortion of the optical channel as well as increasing data rate. In this paper, a novel OFDM VLC system is proposed which can be utilized for both communications and indoor positioning. A positioning algorithm based on power attenuation is used to estimate the receiver coordinates. We further calculate the positioning errors in all the locations of a room and compare them with those using single carrier modulation scheme, i.e., on-off keying (OOK) modulation. We demonstrate that OFDM positioning system outperforms its conventional counterpart. Finally, we investigate the impact of different system parameters on the positioning accuracy of the proposed OFDM VLC system.
DCLfix: A Recommendation System for Repairing Architectural Violations
Venue: arXiv cs.SE 2015
Year: 2015

Architectural erosion is a recurrent problem in software evolution. Despite this fact, the process is usually tackled in ad hoc ways, without adequate tool support at the architecture level. To address this shortcoming, this paper presents a recommendation system -- called DCLfix -- that provides refactoring guidelines for maintainers when tackling architectural erosion. In short, DCLfix suggests refactoring recommendations for violations detected after an architecture conformance process using DCL, an architectural constraint language
Degenerate Motions in Multicamera Cluster SLAM with Non-overlapping Fields of View
Venue: arXiv cs.CV 2015
Year: 2015

An analysis of the relative motion and point feature model configurations leading to solution degeneracy is presented, for the case of a Simultaneous Localization and Mapping system using multicamera clusters with non-overlapping fields-of-view. The SLAM optimization system seeks to minimize image space reprojection error and is formulated for a cluster containing any number of component cameras, observing any number of point features over two keyframes. The measurement Jacobian is transformed to expose a reduced-dimension representation such that the degeneracy of the system can be determined by the rank of a dense submatrix. A set of relative motions sufficient for degeneracy are identified for certain cluster configurations, independent of target model geometry. Furthermore, it is shown that increasing the number of cameras within the cluster and observing features across different cameras over the two keyframes reduces the size of the degenerate motion sets significantly.
Direct Adaptive Controller for Uncertain MIMO Dynamic Systems with Time-varying Delay and Dead-zone Inputs
Venue: arXiv cs.SY 2015
Year: 2015

This paper presents an adaptive tracking control method for a class of nonlinearly parameterized MIMO dynamic systems with time-varying delay and unknown nonlinear dead-zone inputs. A new high dimensional integral Lyapunov-Krasovskii functional is introduced for the adaptive controller to guarantee global stability of the considered systems and also ensure convergence of the tracking errors to the origin. The proposed method provides an alternative to existing methods used for MIMO time-delay systems with dead-zone nonlinearities.
Reliable Broadcast to A User Group with Limited Source Transmissions
Venue: arXiv cs.IT 2015
Year: 2015

In order to reduce the number of retransmissions and save power for the source node, we propose a two-phase coded scheme to achieve reliable broadcast from the source to a group of users with minimal source transmissions. In the first phase, the information packets are encoded with batched sparse (BATS) code, which are then broadcasted by the source node until the file can be cooperatively decoded by the user group. In the second phase, each user broadcasts the re-encoded packets to its peers based on their respective received packets from the first phase, so that the file can be decoded by each individual user. The performance of the proposed scheme is analyzed and the rank distribution at the moment of decoding is derived, which is used as input for designing the optimal BATS code. Simulation results show that the proposed scheme can reduce the total number of retransmissions compared with the traditional single-phase broadcast with optimal erasure codes. Furthermore, since a large number of transmissions are shifted from the source node to the users, power consumptions at the source node is significantly reduced.
On Making Emerging Trusted Execution Environments Accessible to Developers
Venue: arXiv cs.CR 2015
Year: 2015

New types of Trusted Execution Environment (TEE) architectures like TrustLite and Intel Software Guard Extensions (SGX) are emerging. They bring new features that can lead to innovative security and privacy solutions. But each new TEE environment comes with its own set of interfaces and programming paradigms, thus raising the barrier for entry for developers who want to make use of these TEEs. In this paper, we motivate the need for realizing standard TEE interfaces on such emerging TEE architectures and show that this exercise is not straightforward. We report on our on-going work in mapping GlobalPlatform standard interfaces to TrustLite and SGX.
Optimal Layered Representation for Adaptive Interactive Multiview Video Streaming
Venue: arXiv cs.MM 2015
Year: 2015

We consider an interactive multiview video streaming (IMVS) system where clients select their preferred viewpoint in a given navigation window. To provide high quality IMVS, many high quality views should be transmitted to the clients. However, this is not always possible due to the limited and heterogeneous capabilities of the clients. In this paper, we propose a novel adaptive IMVS solution based on a layered multiview representation where camera views are organized into layered subsets to match the different clients constraints. We formulate an optimization problem for the joint selection of the views subsets and their encoding rates. Then, we propose an optimal and a reduced computational complexity greedy algorithms, both based on dynamic-programming. Simulation results show the good performance of our novel algorithms compared to a baseline algorithm, proving that an effective IMVS adaptive solution should consider the scene content and the client capabilities and their preferences in navigation.
Tradeoffs Between Cost and Information for Rendezvous and Treasure Hunt
Venue: arXiv cs.DC 2015
Year: 2015

In rendezvous, two agents traverse network edges in synchronous rounds and have to meet at some node. In treasure hunt, a single agent has to find a stationary target situated at an unknown node of the network. We study tradeoffs between the amount of information ($\mathit{advice}$) available $\mathit{a\ priori}$ to the agents and the cost (number of edge traversals) of rendezvous and treasure hunt. Our goal is to find the smallest size of advice which enables the agents to solve these tasks at some cost $C$ in a network with $e$ edges. This size turns out to depend on the initial distance $D$ and on the ratio $\frac{e}{C}$, which is the $\mathit{relative\ cost\ gain}$ due to advice. For arbitrary graphs, we give upper and lower bounds of $O(D\log(D\cdot \frac{e}{C}) +\log\log e)$ and $Ω(D\log \frac{e}{C})$, respectively, on the optimal size of advice. For the class of trees, we give nearly tight upper and lower bounds of $O(D\log \frac{e}{C} + \log\log e)$ and $Ω(D\log \frac{e}{C})$, respectively.
Spectral Collaborative Representation based Classification for Hand Gestures recognition on Electromyography Signals
Venue: arXiv cs.CV 2015
Year: 2015

In this study, we introduce a novel variant and application of the Collaborative Representation based Classification in spectral domain for recognition of the hand gestures using the raw surface Electromyography signals. The intuitive use of spectral features are explained via circulant matrices. The proposed Spectral Collaborative Representation based Classification (SCRC) is able to recognize gestures with higher levels of accuracy for a fairly rich gesture set. The worst recognition result which is the best in the literature is obtained as 97.3\% among the four sets of the experiments for each hand gestures. The recognition results are reported with a substantial number of experiments and labeling computation.
Dynamic Bayesian Ontology Languages
Venue: arXiv cs.AI 2015
Year: 2015

Many formalisms combining ontology languages with uncertainty, usually in the form of probabilities, have been studied over the years. Most of these formalisms, however, assume that the probabilistic structure of the knowledge remains static over time. We present a general approach for extending ontology languages to handle time-evolving uncertainty represented by a dynamic Bayesian network. We show how reasoning in the original language and dynamic Bayesian inferences can be exploited for effective reasoning in our framework.
Robust Online Monitoring of Signal Temporal Logic
Venue: arXiv cs.SY 2015
Year: 2015

Signal Temporal Logic (STL) is a formalism used to rigorously specify requirements of cyberphysical systems (CPS), i.e., systems mixing digital or discrete components in interaction with a continuous environment or analog com- ponents. STL is naturally equipped with a quantitative semantics which can be used for various purposes: from assessing the robustness of a specification to guiding searches over the input and parameter space with the goal of falsifying the given property over system behaviors. Algorithms have been proposed and implemented for offline computation of such quantitative semantics, but only few methods exist for an online setting, where one would want to monitor the satisfaction of a formula during simulation. In this paper, we formalize a semantics for robust online monitoring of partial traces, i.e., traces for which there might not be enough data to decide the Boolean satisfaction (and to compute its quantitative counterpart). We propose an efficient algorithm to compute it and demonstrate its usage on two large scale real-world case studies coming from the automotive domain and from CPS education in a Massively Open Online Course (MOOC) setting. We show that savings in computationally expensive simulations far outweigh any overheads incurred by an online approach.
Improved Deep Speaker Feature Learning for Text-Dependent Speaker Recognition
Venue: arXiv cs.CL 2015
Year: 2015

A deep learning approach has been proposed recently to derive speaker identifies (d-vector) by a deep neural network (DNN). This approach has been applied to text-dependent speaker recognition tasks and shows reasonable performance gains when combined with the conventional i-vector approach. Although promising, the existing d-vector implementation still can not compete with the i-vector baseline. This paper presents two improvements for the deep learning approach: a phonedependent DNN structure to normalize phone variation, and a new scoring approach based on dynamic time warping (DTW). Experiments on a text-dependent speaker recognition task demonstrated that the proposed methods can provide considerable performance improvement over the existing d-vector implementation.
A Linear-Size Logarithmic Stretch Path-Reporting Distance Oracle for General Graphs
Venue: arXiv cs.DS 2015
Year: 2015

In 2001 Thorup and Zwick devised a distance oracle, which given an $n$-vertex undirected graph and a parameter $k$, has size $O(k n^{1+1/k})$. Upon a query $(u,v)$ their oracle constructs a $(2k-1)$-approximate path $Π$ between $u$ and $v$. The query time of the Thorup-Zwick's oracle is $O(k)$, and it was subsequently improved to $O(1)$ by Chechik. A major drawback of the oracle of Thorup and Zwick is that its space is $Ω(n \cdot \log n)$. Mendel and Naor devised an oracle with space $O(n^{1+1/k})$ and stretch $O(k)$, but their oracle can only report distance estimates and not actual paths. In this paper we devise a path-reporting distance oracle with size $O(n^{1+1/k})$, stretch $O(k)$ and query time $O(n^ε)$, for an arbitrarily small $ε> 0$. In particular, our oracle can provide logarithmic stretch using linear size. Another variant of our oracle has size $O(n \log\log n)$, polylogarithmic stretch, and query time $O(\log\log n)$. For unweighted graphs we devise a distance oracle with multiplicative stretch $O(1)$, additive stretch $O(β(k))$, for a function $β(\cdot)$, space $O(n^{1+1/k} \cdot β)$, and query time $O(n^ε)$, for an arbitrarily small constant $ε>0$. The tradeoff between multiplicative stretch and size in these oracles is far below girth conjecture threshold (which is stretch $2k-1$ and size $O(n^{1+1/k})$). Breaking the girth conjecture tradeoff is achieved by exhibiting a tradeoff of different nature between additive stretch $β(k)$ and size $O(n^{1+1/k})$. A similar type of tradeoff was exhibited by a construction of $(1+ε,β)$-spanners due to Elkin and Peleg. However, so far $(1+ε,β)$-spanners had no counterpart in the distance oracles' world. An important novel tool that we develop on the way to these results is a {distance-preserving path-reporting oracle}.
Automated Benchmarking of Incremental SAT and QBF Solvers
Venue: arXiv cs.LO 2015
Year: 2015

Incremental SAT and QBF solving potentially yields improvements when sequences of related formulas are solved. An incremental application is usually tailored towards some specific solver and decomposes a problem into incremental solver calls. This hinders the independent comparison of different solvers, particularly when the application program is not available. As a remedy, we present an approach to automated benchmarking of incremental SAT and QBF solvers. Given a collection of formulas in (Q)DIMACS format generated incrementally by an application program, our approach automatically translates the formulas into instructions to import and solve a formula by an incremental SAT/QBF solver. The result of the translation is a program which replays the incremental solver calls and thus allows to evaluate incremental solvers independently from the application program. We illustrate our approach by different hardware verification problems for SAT and QBF solvers.
Analytical reconstruction of isotropic turbulence spectra based on the Gaussian transform
Venue: arXiv cs.CE 2015
Year: 2015

The Random Particle Mesh (RPM) method used to simulate turbulence-induced broadband noise in several aeroacoustic applications is extended to realise isotropic turbulence spectra. With this method turbulent fluctuations are synthesised by filtering white noise with a Gaussian filter kernel that in turn gives a Gaussian spectrum. The Gaussian function is smooth and its derivatives and integrals are again Gaussian functions. The Gaussian filter is efficient and finds wide-spread applications in stochastic signal processing. However in many applications Gaussian spectra do not correspond to real turbulence spectra. Thus in turbo-machines the von Kármán, Liepmann, and modified von Kármán spectra are more realistic model spectra. In this note we analytically derive weighting functions to realise arbitrary isotropic solenoidal spectra using a superposition of weighted Gaussian spectra of different length scales. The analytic weighting functions for the von Kármán, the Liepmann, and the modified von Kármán spectra are derived subsequently. Finally a method is proposed to discretise the problem using a limited number of Gaussian spectra. The effectivity of this approach is demonstrated by realising a von Kármán velocity spectrum using the RPM method.
Fail Fast - Fail Often: Enhancing Agile Methodology using Dynamic Regression, Code Bisector and Code Quality in Continuous Integration (CI)
Venue: arXiv cs.SE 2015
Year: 2015

Agile practices are receiving considerable attention from industry as an alternative to traditional software development approaches. However, there are a number of challenges in combining Agile [2] with Test-driven development (TDD) [10] practices, cloud deployments, continuous integration (CI), non-stop performance, load, security and accessibly testing. From these challenges; Continuous Integration is a relatively an approach widely discussed and practiced in software testing. This paper describes an approach for improved Agile Methodology using Code Quality, Code Bisector and Dynamic Regression in Continuous Integration. The set of tools used for this analysis, design and development are Jenkins, Robot Framework [4], Perforce and Git.